Speech Enhancement with Local Adaptive Rank-Order Filtering

Abstract

A local adaptive algorithm for speech enhancement is presented. The algorithm is based on calculation of the rank-order statistics of an input speech signal over a moving window. The algorithm varies the size and contents of a sliding window signal as well as an estimation function employed for recovering a clean speech signal from a noisy signal. The algorithm improves the quality of a speech signal preserving its intelligibility. The performance of the algorithm for suppressing additive noise in an input test speech signal is compared with that of common speech enhancement algorithms in terms of objective metrics. la misma. sed approach. As an example, the representation of iris images through functional data for recognition tasks was used. The paper presents experiments and results of applying this approach to the recognition of iris images, demonstrating its effectiveness.